To train our i-frame compression models, we use a subset of ImageNet database [1]}. To train the whole video compression models, we use the Vimeo-90k septuplets dataset [2]} which consists of 89,800 video clips with diverse content. To report the rate-distortion (R-D) performance [3]}, [4]}, we evaluate our proposed method on the UVG dataset [5]} which includes seven 1080p video sequences, and HEVC standard Common Test Sequences [6]} known as Class B (1920\(\times \) 1080), Class C (832\(\times \) 480), Class D (416\(\times \) 240) and Class E (1280\(\times \) 720).
